Explore AI Agent Skills & Claude Prompts
Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.
Enter through keywords, occupations, creators, and GitHub sources to see what kinds of skills are emerging across domains.
Use the same catalog through the API
Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
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brave-search-api
by s-hiraokuThis skill enables web searching using Brave Search API directly via curl. Use when searching for current information, news, articles, or web content. MCP server not required - calls API directly.
terminal-expert
by s-hiraokuThis skill provides unified expert-level guidance for terminal implementation in VS Code extensions. Covers xterm.js API and addons, VS Code terminal architecture, PTY integration, session persistence, input handling (keyboard/IME/mouse), shell integration with OSC sequences, and performance optimization. Use when implementing any terminal-related features.
vscode-test-setup
by s-hiraokuThis skill provides comprehensive guidance for setting up and configuring test environments for VS Code extension projects. Use when initializing a new test infrastructure, configuring test runners (Vitest), setting up CI/CD test pipelines, integrating coverage tools (v8/c8), or troubleshooting test configuration issues.
synapse-manager
by s-hiraokuMulti-agent management workflow — task delegation, progress monitoring, quality verification with regression testing, feedback delivery, and cross-review orchestration. Use this skill when coordinating multiple agents on a shared task, monitoring delegated work, ensuring quality across agent outputs, or implementing a multi-phase plan (3+ phases or 10+ file changes).
synapse-a2a
by s-hiraokuThis skill provides comprehensive guidance for inter-agent communication using the Synapse A2A framework. Use this skill when sending messages to other agents via synapse send/reply commands, understanding priority levels, handling A2A protocol operations, managing task history, configuring settings, or using File Safety features for multi-agent coordination. Automatically triggered when agent communication, A2A protocol tasks, history operations, or file safety operations are detected.
firecrawl-api
by s-hiraokuThis skill enables web scraping and content extraction using Firecrawl API directly via curl. Use when scraping web pages, crawling websites, or extracting structured data. MCP server not required.
vscode-extension-expert
by s-hiraokuThis skill provides expert-level guidance for VS Code extension development. Use when implementing new extension features, debugging extension code, designing WebView UIs, implementing Language Server Protocol features, or optimizing extension performance. Covers activation events, contribution points, VS Code API patterns, security best practices, testing strategies, and publishing workflows.
vscode-webview-expert
by s-hiraokuThis skill provides expert-level guidance for implementing VS Code WebView features. Use when creating WebView panels, implementing secure CSP policies, handling Extension-WebView communication, managing WebView state persistence, optimizing WebView performance, or debugging WebView rendering issues. Covers security best practices, message protocols, and VS Code-specific WebView patterns.
vscode-extension-refactorer
by s-hiraokuThis skill provides expert-level guidance for refactoring VS Code extension code. Use when extracting classes or functions, reducing code duplication, improving type safety, reorganizing module structure, applying design patterns, or optimizing performance. Covers systematic refactoring workflows, code smell detection, safe transformation techniques, and VS Code-specific patterns.
vscode-bug-hunter
by s-hiraokuThis skill provides systematic bug detection and discovery capabilities for VS Code extensions. Use when searching for hidden bugs, analyzing code for potential issues, investigating suspicious behavior, performing code audits, or proactively finding bugs before they manifest. Covers static analysis patterns, dynamic analysis techniques, code smell detection, and systematic codebase investigation.
vscode-extension-debugger
by s-hiraokuThis skill provides expert-level guidance for debugging and fixing bugs in VS Code extensions. Use when investigating runtime errors, fixing memory leaks, resolving WebView issues, debugging activation problems, fixing TypeScript type errors, or troubleshooting extension communication failures. Covers systematic debugging workflows, common bug patterns, root cause analysis, and prevention strategies.
x-search
by s-hiraokuUse when searching X/Twitter posts, profiles, threads, reactions, rumors, or current discussion by delegating the lookup to Hermes Agent with its built-in x_search tool. Triggers on "X で検索", "ツイート検索", "X で何て言われてる", "search X for", "what's the buzz on X about", and @handle recent-post lookups.
Browse Agent Skills by Occupation
23 major groups · 867 SOC occupations
Browse by Category
Explore agent skills organized by their primary use case
Explore the agent skills ecosystem by occupation and creator
SkillMD is not just a keyword search box. It is an open map that organizes public skills by occupation, creator, and repository, helping you see which workflows, judgment criteria, and domain habits people are writing for AI agents.
Then follow creators and GitHub repositories back to the source: compare the skills a team maintains, whether the repo is active, and how the README frames the work before you open, install, or reuse anything.
Use it three ways: learn an unfamiliar field by occupation, study how creators organize skills, then use source context to decide what is worth opening or reusing.
01 Map a field
Browse 23 occupation groups and 867 SOC roles to learn what skills exist in adjacent domains and how they break down real work.
02 Follow creators
Use creator and repository pages to inspect maintained skill collections, recent updates, and source context before trusting a result.
03 Search with sources
Search 1.7M+ collected skills, then use occupation tags, creators, and GitHub source context to decide what is worth opening.
Start with the occupation map, then follow creators and repositories back to real code. SkillMD helps explain why a skill is worth opening, not only what it is named.
Standardizing Agent Capabilities with SKILL.md and Model Context Protocol (MCP)
In the rapidly evolving landscape of artificial intelligence, LLM agents (Large Language Model agents) have transitioned from simple text predictors to autonomous problem solvers. To orchestrate complex, multi-step agentic workflows, developers require a standardized format to specify agent capabilities, prompt instructions, system rules, and database bindings. This is where SKILL.md and the Model Context Protocol (MCP) have emerged as standard developer paradigms. SkillMD serves as the central directory for indexing, exploring, and sharing these critical agent configurations.
Our open-source registry currently tracks over 1.7 million collected SKILL.md configurations and system prompts. By compiling agent configurations from active developers on GitHub, we bridge the gap between prompt engineering research and production execution. Whether you are building agents with Anthropic's Claude Code, OpenAI's GPT-4, Google's Gemini, or local models using Ollama and LlamaIndex, standardized skill definitions ensure your agents behave predictably across different runtime environments.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open-source standard designed to connect LLMs to data sources, developer tools, and external environments. MCP establishes a bidirectional communication channel between client applications (like Cursor, Claude Desktop, or custom agent systems) and servers hosting data or capabilities. Standardizing instructions via SKILL.md enables LLMs to query databases, read local files, execute terminal commands, and integrate third-party APIs. SkillMD allows you to find ready-to-run MCP servers and prompt instructions for various occupations and technical tasks.
The Structure of a Professional SKILL.md File
A valid SKILL.md configuration is designed to be easily read by humans and parsed by LLMs. It contains precise system instructions, trigger conditions, required parameters, and execution examples. Below is the typical architectural blueprint of a professional agent skill:
- Metadata & Core Scope: Declares the name of the skill, author details, target models, and a description of the capability.
- Triggers & Intent Detection: Details semantic triggers that help the agent decide when to invoke this skill.
- System Prompts: Explicit system-level instructions that direct the agent's behavior, personality, safety guardrails, and formatting preferences.
- Capabilities & Tools: Lists the files, databases, or APIs the agent must access to complete the tasks.
- Few-Shot Examples: Demonstrates real inputs and outputs, helping the model generalize behavior through in-context learning.
Optimizing Agent Workflows for Modern LLMs
Writing effective agent skills requires deep knowledge of prompt engineering. With the release of advanced reasoning models like Claude 3.5 Sonnet, ChatGPT o1, and DeepSeek-V3, prompt templates must focus on structured thinking. Developers are encouraged to use XML tags (e.g., <thought>, <context>, and <rules>) to isolate execution boundaries. Standardized prompts prevent agents from suffering from context drift, ensuring that long-running tasks remain aligned with the initial system parameters.
Exploring by SOC Occupations and Creator Profiles
What makes SkillMD unique is its taxonomy. Instead of simple text search, we parse and organize files according to the Standard Occupational Classification (SOC) system. This means you can discover skills written for Computer and Mathematical roles, Business and Financial operations, Legal, Design, and and Educational Instruction fields. By tracking creator profiles, developers can study how different teams organize their custom instructions, compare version updates, and fork public configs for specialized enterprise use cases.
SkillMD operates as a high-performance index running on a fast Go backend and a highly responsive Astro SSR frontend. All search queries execute in milliseconds, featuring smart debouncing to prevent multiple API requests while keeping user data secure. Join our community of developers to standardize your AI agent instructions and optimize your LLM prompting workflows today.
Frequently Asked Questions
A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.